With the continuous expansion of the scale of the power grid, the consumption of energy and natural resources is increasing, and distributed power generation technology has gained more and more attention and application. Distributed energy can flexibly access and cut out the power grid in the form of microgrid organization, and become an important part of the smart grid. Although the microgrid can realize the effective control and management of the distributed energy, but the inherent randomness and intermittence of the distributed energy still have the impact on the stability of the power grid. Therefore, it is necessary to monitor the status of equipment and network in the microgrid. The power flow is calculated by monitoring the voltage at each pivot point, the voltage and phase angle of the equilibrium point to analyze the power distribution, loss, voltage distribution and other aspects of each branch, In addition, through the monitoring temperature, humidity, frequency and other state information to analyze whether there is a fault, determine the type of fault, so as to solve the problem in time.
In order to obtain a large number of accurate and comprehensive information on the status of the equipment and network, according to the different requirements of each target node in the distribution network, various types of corresponding information perception devices are needed to deploy to monitor the status data such as voltage, temperature, humidity, frequency and so on. However, traditional coverage methods cannot meet the different monitoring requirements of different target nodes in the distribution network. The transmission of a large number of monitoring data will speed up the energy consumption of information perception device nodes and shorten the information perception network life cycle. Therefore, how to realize the efficient use of the energy of the perception device and improve the efficiency of the information perception network becomes a problem to be solved.